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- Siamese Network Description: The Siamese Network is a neural network architecture designed to learn to differentiate between two input samples by comparing(...) Read more
- Sparse Neural Networks Description: Sparse Neural Networks are a type of neural network architecture characterized by having a significant number of weights that are(...) Read more
- Spatial Attention Description: Spatial Attention is a fundamental mechanism in the field of neural networks, especially in deep learning and convolutional neural(...) Read more
- Scale Invariance Description: Scale invariance is a fundamental property in the field of computer vision and convolutional neural networks (CNNs). It refers to(...) Read more
- Sequence Modeling Description: Sequence modeling is an approach within deep learning that focuses on predicting the next element in a sequence based on previous(...) Read more
- Sparse Autoencoder Description: A sparse autoencoder is a type of neural network used in deep learning to learn efficient representations of input data by imposing(...) Read more
- Spatial Transformer Network Description: Spatial Transformer Networks are a type of neural network architecture that specializes in performing spatial transformations on(...) Read more
- Spectral Clustering Description: Spectral Clustering is an unsupervised learning technique based on graph theory and spectral analysis for grouping data. It uses(...) Read more
- Sparsity-Inducing Norms Description: Sparsity-Inducing Norms are regularization techniques used in deep learning that aim to limit the complexity of models during the(...) Read more
- Semantic Similarity Description: Semantic similarity is a measure that evaluates how similar two text fragments are in terms of their meaning. This concept is(...) Read more
- Saliency Map Description: A saliency map is a visual representation that highlights the most important regions in an image for a given task, such as(...) Read more
- Sparse Neural Network Description: A sparse neural network is a type of neural network characterized by having a significant number of weights that are zero. This(...) Read more
- Softmax Function Description: The Softmax function is a mathematical function that transforms a vector of real values into a probability distribution. This(...) Read more
- Skip Connection Description: The skip connection is a fundamental concept in the design of deep neural networks. It refers to a shortcut connection that allows(...) Read more
- Signal Processing Description: Signal processing refers to the analysis, interpretation, and manipulation of signals, which are representations of data in the(...) Read more
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